Overview

Dataset statistics

Number of variables7
Number of observations977
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.1 KiB
Average record size in memory64.0 B

Variable types

DateTime1
Numeric6

Alerts

Volatility is highly overall correlated with ATRHigh correlation
ATR is highly overall correlated with VolatilityHigh correlation
ATR_15 is highly overall correlated with ATR_Diff and 1 other fieldsHigh correlation
ATR_Diff is highly overall correlated with ATR_15High correlation
ATR_AvgDiff is highly overall correlated with ATR_15High correlation
Date has unique valuesUnique
Volatility has unique valuesUnique
ATR has unique valuesUnique
ATR_Diff has unique valuesUnique
ATR_AvgDiff has unique valuesUnique
Volatility_Pct has 203 (20.8%) zerosZeros

Reproduction

Analysis started2023-08-13 02:05:57.772337
Analysis finished2023-08-13 02:06:00.520611
Duration2.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Date
Date

UNIQUE 

Distinct977
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
Minimum2019-09-04 00:00:00
Maximum2023-07-21 00:00:00
2023-08-12T22:06:00.572633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:06:00.663157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Volatility
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct977
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.77628228
Minimum0.24609136
Maximum2.3734533
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.3 KiB
2023-08-12T22:06:00.755033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.24609136
5-th percentile0.31464644
Q10.52843298
median0.68380574
Q30.94082519
95-th percentile1.6302403
Maximum2.3734533
Range2.1273619
Interquartile range (IQR)0.4123922

Descriptive statistics

Standard deviation0.40993086
Coefficient of variation (CV)0.52806932
Kurtosis4.183552
Mean0.77628228
Median Absolute Deviation (MAD)0.19197966
Skewness1.8573211
Sum758.42779
Variance0.16804331
MonotonicityNot monotonic
2023-08-12T22:06:00.838569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.257240033 1
 
0.1%
0.4242259684 1
 
0.1%
0.4061173594 1
 
0.1%
0.4089582776 1
 
0.1%
0.4069960798 1
 
0.1%
0.3972719584 1
 
0.1%
0.4108677347 1
 
0.1%
0.453835634 1
 
0.1%
0.4587467801 1
 
0.1%
0.4494354999 1
 
0.1%
Other values (967) 967
99.0%
ValueCountFrequency (%)
0.2460913625 1
0.1%
0.2491989316 1
0.1%
0.2508537949 1
0.1%
0.2521673527 1
0.1%
0.2537327423 1
0.1%
0.2558750732 1
0.1%
0.2571759514 1
0.1%
0.257726075 1
0.1%
0.2596575762 1
0.1%
0.2617359017 1
0.1%
ValueCountFrequency (%)
2.373453261 1
0.1%
2.363505531 1
0.1%
2.346907472 1
0.1%
2.345985615 1
0.1%
2.341483993 1
0.1%
2.335540829 1
0.1%
2.326950524 1
0.1%
2.324867095 1
0.1%
2.304530074 1
0.1%
2.299615309 1
0.1%

Volatility_Pct
Real number (ℝ)

ZEROS 

Distinct652
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.42267301
Minimum0
Maximum1
Zeros203
Zeros (%)20.8%
Negative0
Negative (%)0.0%
Memory size15.3 KiB
2023-08-12T22:06:00.924995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.042003273
median0.32540206
Q30.79554888
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0.75354561

Descriptive statistics

Standard deviation0.37682475
Coefficient of variation (CV)0.89152783
Kurtosis-1.4487124
Mean0.42267301
Median Absolute Deviation (MAD)0.32540206
Skewness0.33047107
Sum412.95153
Variance0.14199689
MonotonicityNot monotonic
2023-08-12T22:06:01.016570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 203
 
20.8%
1 124
 
12.7%
0.01355316816 1
 
0.1%
0.4545712275 1
 
0.1%
0.595288288 1
 
0.1%
0.5175807734 1
 
0.1%
0.2234587469 1
 
0.1%
0.2803697182 1
 
0.1%
0.1261655897 1
 
0.1%
0.04381762663 1
 
0.1%
Other values (642) 642
65.7%
ValueCountFrequency (%)
0 203
20.8%
0.0003312659375 1
 
0.1%
0.0008437077268 1
 
0.1%
0.003144050421 1
 
0.1%
0.005106145046 1
 
0.1%
0.006299135201 1
 
0.1%
0.006398349434 1
 
0.1%
0.008102482111 1
 
0.1%
0.009745632104 1
 
0.1%
0.01062591888 1
 
0.1%
ValueCountFrequency (%)
1 124
12.7%
0.998513154 1
 
0.1%
0.997962366 1
 
0.1%
0.9958842939 1
 
0.1%
0.9948140664 1
 
0.1%
0.9930455055 1
 
0.1%
0.9918419421 1
 
0.1%
0.9908278634 1
 
0.1%
0.9880662011 1
 
0.1%
0.9878116484 1
 
0.1%

ATR
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct977
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6755319
Minimum0.96001694
Maximum7.8059194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.3 KiB
2023-08-12T22:06:01.143117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.96001694
5-th percentile1.1546768
Q12.8138615
median3.3962958
Q34.2558094
95-th percentile7.1901565
Maximum7.8059194
Range6.8459024
Interquartile range (IQR)1.4419479

Descriptive statistics

Standard deviation1.5958721
Coefficient of variation (CV)0.43418807
Kurtosis0.21386047
Mean3.6755319
Median Absolute Deviation (MAD)0.74535405
Skewness0.69160938
Sum3590.9947
Variance2.5468079
MonotonicityNot monotonic
2023-08-12T22:06:01.234949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.384394207 1
 
0.1%
6.495791896 1
 
0.1%
6.448112052 1
 
0.1%
6.295571248 1
 
0.1%
6.123199832 1
 
0.1%
5.989653176 1
 
0.1%
6.062342964 1
 
0.1%
6.338853433 1
 
0.1%
6.270929871 1
 
0.1%
6.114201213 1
 
0.1%
Other values (967) 967
99.0%
ValueCountFrequency (%)
0.9600169385 1
0.1%
0.9726824759 1
0.1%
0.9878369775 1
0.1%
0.9914467198 1
0.1%
1.001981179 1
0.1%
1.003692914 1
0.1%
1.004274928 1
0.1%
1.008084397 1
0.1%
1.009545437 1
0.1%
1.012437423 1
0.1%
ValueCountFrequency (%)
7.805919374 1
0.1%
7.740402219 1
0.1%
7.72438836 1
0.1%
7.691187132 1
0.1%
7.646762469 1
0.1%
7.633882575 1
0.1%
7.631524749 1
0.1%
7.630089766 1
0.1%
7.604750448 1
0.1%
7.57310799 1
0.1%

ATR_15
Real number (ℝ)

HIGH CORRELATION 

Distinct833
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3533367
Minimum0.01
Maximum39.12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.3 KiB
2023-08-12T22:06:01.325526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.478
Q12.73
median6.14
Q311.71
95-th percentile23.316
Maximum39.12
Range39.11
Interquartile range (IQR)8.98

Descriptive statistics

Standard deviation7.3392007
Coefficient of variation (CV)0.8785951
Kurtosis1.3297297
Mean8.3533367
Median Absolute Deviation (MAD)4.13
Skewness1.2660898
Sum8161.21
Variance53.863867
MonotonicityNot monotonic
2023-08-12T22:06:01.418058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.03 4
 
0.4%
1.5 4
 
0.4%
5.47 4
 
0.4%
0.71 4
 
0.4%
2.75 4
 
0.4%
0.45 4
 
0.4%
2.53 4
 
0.4%
5.11 3
 
0.3%
5.86 3
 
0.3%
0.5 3
 
0.3%
Other values (823) 940
96.2%
ValueCountFrequency (%)
0.01 1
 
0.1%
0.03 4
0.4%
0.04 1
 
0.1%
0.05 1
 
0.1%
0.07 1
 
0.1%
0.08 1
 
0.1%
0.09 1
 
0.1%
0.09 1
 
0.1%
0.1 2
0.2%
0.1 1
 
0.1%
ValueCountFrequency (%)
39.12 1
0.1%
37.19 1
0.1%
35.18 1
0.1%
33.86 1
0.1%
33.73 2
0.2%
33.71 1
0.1%
33.55 1
0.1%
32.58 1
0.1%
31.79 1
0.1%
30.99 1
0.1%

ATR_Diff
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct977
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6778048
Minimum-7.301645
Maximum33.072585
Zeros0
Zeros (%)0.0%
Negative280
Negative (%)28.7%
Memory size15.3 KiB
2023-08-12T22:06:01.508093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7.301645
5-th percentile-3.1423245
Q1-0.53460948
median2.7687756
Q38.0287145
95-th percentile19.268103
Maximum33.072585
Range40.37423
Interquartile range (IQR)8.5633239

Descriptive statistics

Standard deviation7.0937105
Coefficient of variation (CV)1.5164614
Kurtosis1.4482709
Mean4.6778048
Median Absolute Deviation (MAD)3.7921709
Skewness1.2510747
Sum4570.2153
Variance50.320729
MonotonicityNot monotonic
2023-08-12T22:06:01.601796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.02560579326 1
 
0.1%
13.1842081 1
 
0.1%
21.02188795 1
 
0.1%
19.48442875 1
 
0.1%
17.17680017 1
 
0.1%
23.23034682 1
 
0.1%
23.31765704 1
 
0.1%
14.86114657 1
 
0.1%
11.22907013 1
 
0.1%
19.24579879 1
 
0.1%
Other values (967) 967
99.0%
ValueCountFrequency (%)
-7.301644971 1
0.1%
-7.089874179 1
0.1%
-6.693882575 1
0.1%
-6.676762469 1
0.1%
-6.534270943 1
0.1%
-6.117384597 1
0.1%
-5.883567457 1
0.1%
-5.564138853 1
0.1%
-5.449270368 1
0.1%
-5.113991527 1
0.1%
ValueCountFrequency (%)
33.07258497 1
0.1%
32.26220286 1
0.1%
31.59876977 1
0.1%
30.45149819 1
0.1%
30.21511047 1
0.1%
29.72634104 1
0.1%
29.52240057 1
0.1%
29.34073164 1
0.1%
27.96576596 1
0.1%
27.6447149 1
0.1%

ATR_AvgDiff
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct977
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6854792
Minimum-2.3758377
Maximum24.73748
Zeros0
Zeros (%)0.0%
Negative143
Negative (%)14.6%
Memory size15.3 KiB
2023-08-12T22:06:01.697405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.3758377
5-th percentile-1.1587538
Q11.0907758
median3.3659033
Q36.4829314
95-th percentile15.510666
Maximum24.73748
Range27.113318
Interquartile range (IQR)5.3921556

Descriptive statistics

Standard deviation5.1559749
Coefficient of variation (CV)1.1004157
Kurtosis1.8264485
Mean4.6854792
Median Absolute Deviation (MAD)2.4917813
Skewness1.3760882
Sum4577.7132
Variance26.584077
MonotonicityNot monotonic
2023-08-12T22:06:01.791013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.53846759 1
 
0.1%
3.169782033 1
 
0.1%
5.365466423 1
 
0.1%
6.409590884 1
 
0.1%
6.894018158 1
 
0.1%
7.764861392 1
 
0.1%
9.271470633 1
 
0.1%
10.56937259 1
 
0.1%
11.54212553 1
 
0.1%
12.74367272 1
 
0.1%
Other values (967) 967
99.0%
ValueCountFrequency (%)
-2.375837746 1
0.1%
-2.301207108 1
0.1%
-2.055282569 1
0.1%
-1.982509003 1
0.1%
-1.942919514 1
0.1%
-1.918591546 1
0.1%
-1.902841509 1
0.1%
-1.8814632 1
0.1%
-1.760531426 1
0.1%
-1.760515229 1
0.1%
ValueCountFrequency (%)
24.73748012 1
0.1%
24.45511068 1
0.1%
24.38534775 1
0.1%
24.13628787 1
0.1%
24.12707034 1
0.1%
24.04761859 1
0.1%
22.73835325 1
0.1%
22.30533534 1
0.1%
21.48671182 1
0.1%
20.86338861 1
0.1%

Interactions

2023-08-12T22:05:59.993778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:57.842353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.281438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.701483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.117378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.546323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:06:00.053789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:57.904876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.346459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.765012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.182896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.609585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:06:00.116811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:57.969904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.414481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.834800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.256417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.677110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:06:00.183590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.044924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.486004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.905317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.331445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.747996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:06:00.253604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.113633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.559519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.976337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.408284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.860230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:06:00.322053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.183904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:58.632046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.049851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.480311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-12T22:05:59.928748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-08-12T22:06:01.851028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
VolatilityVolatility_PctATRATR_15ATR_DiffATR_AvgDiff
Volatility1.000-0.006-0.665-0.263-0.060-0.179
Volatility_Pct-0.0061.0000.2720.006-0.093-0.110
ATR-0.6650.2721.0000.2820.0200.263
ATR_15-0.2630.0060.2821.0000.9510.539
ATR_Diff-0.060-0.0930.0200.9511.0000.492
ATR_AvgDiff-0.179-0.1100.2630.5390.4921.000

Missing values

2023-08-12T22:06:00.406555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-12T22:06:00.485108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DateVolatilityVolatility_PctATRATR_15ATR_DiffATR_AvgDiff
2662019-09-042.2572400.2850381.3843941.410.025606-0.538468
2672019-09-052.1899220.0000001.3647682.030.665232-0.464259
2682019-09-062.2590480.3425641.3431171.840.496883-0.376775
2692019-09-092.2620570.3574741.3169091.510.193091-0.296412
2702019-09-102.2817130.4548821.2771151.460.182885-0.257185
2712019-09-112.2974910.5330711.2533071.460.206693-0.199194
2722019-09-122.2643940.3690581.2417541.520.278246-0.175737
2732019-09-132.2174390.1363651.2189701.680.461030-0.122866
2742019-09-162.2009890.0821401.1963721.890.693628-0.055519
2752019-09-172.1769110.0000001.1552802.761.6047200.109338
DateVolatilityVolatility_PctATRATR_15ATR_DiffATR_AvgDiff
12332023-07-100.4693600.2847744.4488200.82-3.628820-1.044854
12342023-07-110.4793360.4796404.4248996.281.855101-1.135997
12352023-07-120.4654170.0435974.4025725.240.837428-1.006975
12362023-07-130.4600720.0000004.2810672.76-1.521067-0.989266
12372023-07-140.4598220.0000004.4543290.13-4.324329-1.261492
12382023-07-170.4507670.0000004.5640411.51-3.054041-1.660593
12392023-07-180.4515260.0185374.4757714.700.224229-1.982509
12402023-07-190.4575150.1648604.5847205.961.375280-1.942920
12412023-07-200.4834020.9948144.7590720.01-4.749072-1.918592
12422023-07-210.4790140.8655414.6258013.38-1.245801-1.684774